US Gigawatts Capacity

Load Libraries

library(tidyverse)
library(here)
library(gganimate)

capacity <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-05-03/capacity.csv')

capacity1 <- capacity %>%
  select(type, year, total_gw) %>% # select the values need it to create our plot
  mutate(type, year, total_gw) %>% # select the values need it to create our plot
  drop_na() #drops NAs

capacity1 %>%
  ggplot(aes(x= type, y= total_gw))+ #creates our graph
  geom_point()+
   labs(x= "Types of Power", y= "Total of Gigawatts", #labels our x and y-axis
       title = "Utilities", #creates our title
       subtitle= "US Total of Gigawatts Capacity in Different type of Power from 2014-2020 ", #creates and label the subtitle
       caption = "Source: 2022-05-03 TidyTuesday  Data from the Berkeley Lab")+
transition_states(
     year, # what are we animating by
     transition_length = 2, #The relative length of the transition.
     state_length = 1 # The length of the pause between transitions
   )+
  ease_aes("sine-in-out") +
  ggtitle('Year: {closest_state}')+ #add a moving year title
  theme(axis.text.x = element_text(angle=90)) #change position of the X-axis to 90 degrees